Aquatic ecosystem changes in a global biodiversity hotspot: Evidence from the Albertine Rift, central Africa
Bibliographic record
Abstract
Abstract Aim Determine the extent to which remote, high‐altitude (Afroalpine) aquatic ecosystems in tropical Africa have been impacted by global and regional‐scale environmental change processes. Location Two volcanic crater lakes (Bisoke and Muhavura) in the Afroalpine zone, Albertine (Western) Rift, central Africa. Methods Sediment cores were collected from Bisoke and Muhavura lakes and dated using radiometric techniques. A range of sediment‐based proxies was extracted from the cores and quantified. Sedimentary data were subjected to statistical analyses that contributed to the identification of influential environmental variables and their effects on diatom assemblages, the determination of variations in spatial beta diversity and estimates of the rate of compositional turnover over the last c. 1,200 years. Results Sediments from the two sites provide evidence of the sensitivity of remote, Afroalpine aquatic ecosystems to perturbation. Climate variability has been a major driver of ecological change, particularly at Bisoke Lake, throughout the c. 1,200‐year‐long record, while Muhavura Lake has been directly impacted by and recovered from at least one volcanic eruption during this time. The effects of climatic warming from the mid‐ to late 19th century and especially from the late 20th century, possibly accentuated by atmospheric deposition‐driven nutrient enrichment, appear increasingly in lockstep. Effects include changes in diatom community composition, increased productivity and compositional turnover, and biotic homogenization (reduced spatial beta diversity) between the two sites. Main conclusions The two Afroalpine sites record changes in atmospheric conditions and their effects on diatom assemblage composition, particularly over the last c. 150 years. Drivers of these changes have the potential to disrupt ecosystems at lower altitudes in the Albertine Rift, including biodiverse areas of forest, and across tropical Africa more widely.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".